Collaborative Sensing, Learning, and Control in Human-Machine Systems

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​Link to the PDF of the talks are now available (located beside the talk title in the Schedule tab).
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​American Control Conference 2016 Workshop

​Tuesday, July 5 2016

Boston Marriott Copley Place
110 Huntington Avenue,
Boston, Massachusetts
Room: Fairfield

About the Workshop

​Recent research at the juncture of decision and learning theory are leading to fundamentally new ways of understanding and tackling challenges in sensing, estimation and control problems. This is especially true for human-machine systems, where autonomous machines can efficiently exploit human insights, knowledge and information-gathering capabilities to improve robustness and performance in complex, time- and safety-critical situations. To enable seamless human-machine collaboration, the community is striving to solve fundamental questions such as asking human the right question(s) at the right time in the right form and vice-versa; understanding each other’s (human and machine) perspective; fusing soft, imperfect information with hard, sensory data; and adapting to complex and possibly unforeseen environment and situations.

In this context, this workshop aims to bring together experts in the fields of control theory, machine learning, artificial intelligence, and human-machine systems to discuss the fundamentals, state of the art and open questions for the various related topic areas including but are not limited to:value of information and optimization/learning strategies for collaboration;
  • Bayesian and non-Bayesian techniques for modeling and adaptation;
  • Modeling and explorative/exploitative learning of human capabilities;
  • Human-machine communication; team planning and control;
  • Interaction in multi human/multi-machine systems;
  • Applications to robotics, decision support systems, cyber-physical systems, and socially important domains such as transportation, energy, medicine, manufacturing, and beyond.

Intended Audience

​Researchers from academia, industry and government who are in general interested in human-machine systems, collaborative planning and active learning, machine learning for controls, multi-agent systems and robotics would be the target audience for this workshop. The workshop will host several renowned experts in the field with a wide variety of perspectives (academia, industry and government) as speakers and they will discuss fundamental developments as well as open problems in this area. Therefore, it will be also an ideal opportunity for young researchers, postdoctoral fellows and graduate students who are already working or intend to work in these areas to learn, discuss and share their thoughts. The panel discussion will be an exciting opportunity for both experts and new researchers to identify the key challenges and finally, a few talks on certain emerging concepts will help the community get a glimpse into the future course of this important research topic.